jupyter-stack-trace

Jupyter Stack Trace

A JupyterLab extension to jump to the line in the file of the stack trace, search Google for the error in Stack Overflow, or ask Bing Chat for help.

(Migrated from https://github.com/teticio/nbextension-gotoerror to JupyterLab and Jupyter Notebook 7.)

One of the disadvantages of working with Jupyter Notebooks is that they can be very difficult to debug when something goes wrong deep down in a stack trace. This extension allows you to click on any of the items in the stack trace and opens up the relevant file at the line where the error occurred. Buttons are also added which search Google for the error in Stack Overflow, or ask Bing Chat for help (for this to work, you must be logged into Bing).

Requirements

• JupyterLab >= 4.0.0

Install

To install the extension, execute:

pip install jupyter_stack_trace

Uninstall

To remove the extension, execute:

pip uninstall jupyter_stack_trace

Settings

Jupyter is only able to access files in the directory in which it is run or a subdirectory. Therefore, to be able to open a file in the stack trace, it is necessary to provide a soft link from the Jupyter launch directory to package source directories.

Make a soft link in the Jupyter launch directory to a base directory of your Python instalation (e.g., ~/.local/lib/python3.10) and call this python3.10. Then add the prefix ~/.local/lib in the jupyter-stack-trace settings. If you use pipenv, for example, then also make a soft link to the ~/.local/share/virtualenvs called virtualenvs and add the prefix ~/.local/share.

The exact configuration will depend on your setup, but if you find that clicking a filename in the stack trace does not open up the file, then make the soft link to a point somewhere higher up the path and add the corresponding prefix in the settings.

To make a soft link in Linux:

ln -s ~/.local/lib/python3.10 python3.10

To make a soft link in Windows:

mklink -d envs C:\users\teticio\Anaconda\python\envs

By default, files are opened as read only, but you can override this in the settings. This allows you to directly modify the packages so you can add temporary debugging code.

Contributing

Development install

Note: You will need NodeJS to build the extension package.

The jlpm command is JupyterLab's pinned version of yarn that is installed with JupyterLab. You may use yarn or npm in lieu of jlpm below.

# Clone the repo to your local environment
# Change directory to the jupyter_stack_trace directory
# Install package in development mode
pip install -e "."
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm build

You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.

# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm watch
# Run JupyterLab in another terminal
jupyter lab

With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).

By default, the jlpm build command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:

jupyter lab build --minimize=False

Development uninstall

pip uninstall jupyter_stack_trace

In development mode, you will also need to remove the symlink created by jupyter labextension develop command. To find its location, you can run jupyter labextension list to figure out where the labextensions folder is located. Then you can remove the symlink named jupyter-stack-trace within that folder.

Packaging the extension

See RELEASE